matlab2tikz
DeepSqueak
| matlab2tikz | DeepSqueak | |
|---|---|---|
| 2 | 2 | |
| 1,504 | 367 | |
| 1.3% | - | |
| 0.0 | 3.2 | |
| 7 months ago | 9 days ago | |
| MATLAB | MATLAB | |
| BSD 2-clause "Simplified" License | BSD 3-clause "New" or "Revised" License |
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matlab2tikz
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Control Systems plots in Latex
I don't know if it helps, but matlab2tikz is really useful and is somewhat easy to edit.
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[P] Bayesian optimization book
Thanks! I used MATLAB to lay out the figures, then used matlab2tikz to convert to TikZ/PGFplots code for typesetting and tweaking as needed. tikzplotlib offers a similar pipeline for Python/matplotlib.
DeepSqueak
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Deep Squeak was designed to sort mice calls. Now it's detecting whales, too
paper / github. This is kind of cool, but really the AI just detects if there's a squeak or not. I'm sure it's useful for research, but it doesn't seem very interesting outside of that.
- HELP! I just moved to Billings, Montana with my two pet rats just to find out they're illegal to own as pets here!!!!
What are some alternatives?
reinforcement_learning_financial_trading - MATLAB example on how to use Reinforcement Learning for developing a financial trading model
Programming-A-Starter-Project-Using-MATLAB-and-Python - A scaffolded project involving pulling and installing a Live Task and using MATLAB and Python in combination to access and analyze data from the OpenWeather web API.
UoS_Beamforming - Repository for the models and code used in "UE Tracking Beamforming using a MIMO Software-Defined Radio" MSc project.
exportToPPTX - MATLAB tool for exporting data to PowerPoint 2007+ files without the need COM-object automation.
gramm - Gramm is a complete data visualization toolbox for Matlab. It provides an easy to use and high-level interface to produce publication-quality plots of complex data with varied statistical visualizations. Gramm is inspired by R's ggplot2 library.
PRMLT - Matlab code of machine learning algorithms in book PRML
MatGPT - MATLAB app to access ChatGPT API from OpenAI
BIPR
imagefusion_deeplearning - VggML (ICPR 2018, Beijing)
bayesoptbook